Universität des Saarlandes
Max Planck Institute for Human Development · Center of Lifespan Psychology
The main objective of "Lifebrain" is to identify the determinants of brain, cognitive and mental (BCM) health at different stages of life. By integrating, harmonising and enriching major European neuroimaging studies across the life span, we will merge fine-grained BCM health measures of more than 5,000 individuals. Longitudinal brain imaging, genetic and health data are available for a major part, as well as cognitive and mental health measures for the broader cohorts, exceeding 27,000 examinations in total. By linking these data to other databases and biobanks, including birth registries, national and regional archives, and by enriching them with a new online data collection and novel measures, we will address the risk factors and protective factors of BCM health. We will identify pathways through which risk and protective factors work and their moderators. Exploiting existing European infrastructures and initiatives, we hope to make major conceptual, methodological and analytical contributions towards large integrative cohorts and their efficient exploitation. We will thus provide novel information on BCM health maintenance, as well as the onset and course of BCM disorders. This will lay a foundation for earlier diagnosis of brain disorders, aberrant development and decline of BCM health, and translate into future preventive and therapeutic strategies. Aiming to improve clinical practice and public health we will work with stakeholders and health authorities, and thus provide the evidence base for prevention and intervention.
Well-being is often relatively stable across adulthood and old age, but typically exhibits pronounced deteriorations and vast individual differences in the terminal phase of life. However, the factors contributing to these differences are not well understood. Using up to 25-year annual longitudinal data obtained from 4,404 now-deceased participants of the nationwide German Socio-Economic Panel Study (SOEP; age at death: M = 73.2 years; SD = 14.3 years; 52% women), we explored the role of multi-indicator constellations of sociodemographic variables, physical health and burden factors, and psychosocial characteristics. Expanding earlier reports, structural equation model (SEM) trees allowed us to identify profiles of variables that were associated with differences in the shape of late-life well-being trajectories. Physical health factors were found to play a major role for well-being decline, but in interaction with psychosocial characteristics such as social participation. To illustrate, for people with low social participation, disability emerged as the strongest correlate of differences in late-life well-being trajectories. However, for people with high social participation, whether or not an individual had spent considerable time in the hospital differentiated high versus low and stable versus declining late-life well-being. We corroborated these results with variable importance measures derived from a set of resampled SEM trees (so-called SEM forests) that provide robust and comparative indicators of the total interactive effects of variables for differential late-life well-being. We discuss benefits and limitations of our approach and consider our findings in the context of other reports about protective factors against terminal decline in well-being.
The brain-derived neurotrophic factor (BDNF) promotes activity-dependent synaptic plasticity, and contributes to learning and memory. We investigated whether a common Val66Met missense polymorphism (rs6265) of the BDNF gene is associated with individual differences in cognitive decline (marked by perceptual speed) in old age. A total of 376 participants of the Berlin Aging Study, with a mean age of 83.9 years at first occasion, were assessed longitudinally up to 11 times across more than 13 years on the Digit-Letter task. Met carriers (n = 123, 34%) showed steeper linear decline than Val homozygotes (n = 239, 66%); the corresponding contrast explained 2.20% of the variance in change in the entire sample, and 3.41% after excluding individuals at risk for dementia. These effects were not moderated by sex or socioeconomic status. Results are consistent with the hypothesis that normal aging magnifies the effects of common genetic variation on cognitive functioning. (PsycINFO Database Record (c) 2014 APA, all rights reserved).